2025/2026
Panel Data: Analysis and Applications for the Social Sciences
ID 981661
Category 'Best Course for Career Development'
Category 'Best Course for Broadening Horizons and Diversity of Knowledge and Skills'
Category 'Best Course for New Knowledge and Skills'
Type:
Mago-Lego
Delivered by:
Department of Higher Mathematics
Where:
Independent HSE Departments
When:
2 module
Open to:
students of one campus
Instructors:
Daria Salnikova
Language:
English
ECTS credits:
3
Contact hours:
36
Course Syllabus
Abstract
Данная дисциплина знакомит студентов с методами анализа панельных данных. Курс состоит из нескольких частей: в первой части - повторение основ множественной линейной регрессии, вторая часть посвящена оцениванию регрессионных моделей с переменными взаимодействия, что пригодится для изучения моделей для анализа панельных данных. Далее третья и четвертая часть курса - соответственно, посвящены изучению моделей с фиксированными и случайными эффектами, моделей с лагированными переменными для тестирования отложенного эффекта и учета авторреляции. Одним из форматов занятий является репликация результатов исследований с последующей критикой примененной стратегии эмпирического анализа. В рамках курса для анализа данных используется Python
Learning Objectives
- The course aims to provide students with the theoretical background and practical skills in conducting panel data analysis. Specifically, the learning objectives are as follows: to enable students to choose appropriate models for panel data analysis; to develop data manipulation and visualization skills; to enable students to implement linear panel models in Python
- The course aims to provide students with the theoretical background and practical skills in conducting panel data analysis. Specifically, the learning objectives are as follows: to enable students to choose appropriate models for panel data analysis to develop data manipulation and visualization skills to enable students to implement linear panel models in Python
Expected Learning Outcomes
- By the end of the course students are expected to apply fixed- and random- effects models to analyze panel data, to interpret the results, to have data visualization skills and skills in implementing the afore-mentioned methods by using RStudio in the context of panel data analysis. Students will learn the advantages and limitations of different approaches to panel data analysis. This knowledge will help students choose a set of appropriate statistical tools to test their research hypotheses.
- A student is able to interpret the results of the difference-in-differences model
- A student is able to explain the essence of the parallel trend assumption
Course Contents
- Introduction. Linear regression analysis
- Regression models with interaction terms
- Random-effects models VS Fixed-effects models
- Difference-in-differences method
Interim Assessment
- 2025/2026 2nd module0.15 * Quiz 1 + 0.1 * Home Assignment 2 + 0.1 * Home Assignment 1 + 0.15 * Quiz 2 + 0.1 * Seminar Activity + 0.4 * Exam
Bibliography
Recommended Core Bibliography
- Charles N. Halaby. (2003). Running Head: Panel Models Panel Models in Sociological Research: Theory into Practice. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.72A0015F
- Data analysis using regression and multilevel/hierarchical models, Gelman, A., 2009
- Mastering 'Metrics : the path from cause to effect, Angrist, J. D., 2015
- Анализ панельных данных и данных о длительности состояний, учебное пособие, Нац. исслед. ун-т Высшая школа экономики, 373 с., Ратникова, Т. А., Фурманов, К. К., 2014
Recommended Additional Bibliography
- Beck, V. L. (2017). Linear Regression : Models, Analysis, and Applications. Hauppauge, New York: Nova Science Publishers, Inc. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1562876